How Will AI Agents Affect IT Service Delivery?
SAP
By SAPBRANDVOICE | Paid Program
Sep 05, 2025 at 09:31am EDT

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By SAP Insights Team

AI agents hold great promise for improving enterprise applications and business workflows. With the ability of agents to automate a broad swath of end-to-end business processes—learning and changing as they go—CIOs will oversee significant shifts in how IT delivers services to the rest of the business. Agents may even reach a point where they replace applications as core elements of IT architecture.


Many IT leaders are already deploying agents to improve IT operations, software development, and IT governance. For example, AI coding agents are taking on programming tasks, reducing software development time and costs. Soon, coding agents not only will write the code, but separate agents will review code for errors, Sheldon Monteiro, executive vice president and chief product officer at Publicis Sapient, tells CIO.

“With DevOps toolchains already automating workflows, adding AI agents is a natural evolution,” Monteiro says. “These agents can autonomously reverse engineer specifications from code, forward engineer test cases and code from specifications, and approve artifacts that meet certain threshold criteria, improving the overall level of automation.”

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More broadly, agents will help improve visibility across enterprise architectures and help IT teams identify pain points, troubleshoot underperforming areas, and make changes and upgrades that can increase uptime and improve IT project success rates.


“Enterprise technology architectures in most companies are massively complicated—every part is linked to every other part,” says Timo Elliott, VP of Marketing and Global Innovation Evangelist with SAP. “AI is really good at synthesizing massively complicated datasets and finding connections that humans don't know exist. [AI agents] will help us move and change things more confidently.”

AI agents can also improve the IT organization’s ability to perform comprehensive and ongoing risk assessments to increase protection and decrease the frequency and effect of cybersecurity incidents.

Elliott shares an example from an enterprise architect who oversaw a migration to S/4 HANA. He tasked an AI agent with reviewing the existing system and all its interconnections, then assess any potential trouble spots that could delay or derail the project. The agent identified a crucial incompatibility between applications that the architect’s team had missed during their initial evaluation.

“Agents can help undo those Gordian knots more easily and more quickly than humans can to make migration projects go more smoothly,” Elliott says. “Anything that helps a CIO de-risk their world would be one of the biggest possible changes to their lives.”


Longer term, we’re likely to see IT organizations shift from supporting applications to supporting agents.

“Today, IT is very much focused on applications for finance, procurement, et cetera,” says Francesco Brenna, VP & Senior Partner for AI Integration Services with IBM Consulting. “As agents are integrated across all these applications, the application landscape will blur. Agents will become the key component of IT architecture.”

This shift will require a new discovery and operating model to ensure people can find the right agents to help them do their jobs. “As agents evolve, they may need to be managed like humans, with IT serving as an HR-like function for agents,” Elliott says. Andreas Welsch, chief AI strategist at AI consultancy Intelligence Briefing, advocates for an “Agent Resources” department that draws on traditional HR principles to define the roles of agents and measure their performance.

As agentic AI strategies evolve, it’s important for CIOs to revisit a core principle: building a robust data infrastructure and management environment.

“Without a solid data foundation, organizations are going to be very constrained by the kinds of AI activities they can do,” says Elliott. “Use the momentum from AI to put on the rubber gloves and get serious about your data plumbing. Sort out integrations and data quality and put proper process management and monitoring tools in place. Surging ahead without all that is just going to get frustrating.”